The fraction of predicted Ag-competent cells is shown below for each sample.


The total number of predicted Ag-competent cells is shown below for each sample.


The expression of Ag-low and Ag-high gene modules is shown for predicted Ag-low and Ag-competent cells.


UMAP projections show predicted Ag-low and Ag-competent cLECs for each sample.


Expression of LEC markers is shown below for each sample.


R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_US.UTF-8          LC_NUMERIC=C                 
 [3] LC_TIME=en_US.UTF-8           LC_COLLATE=en_US.UTF-8       
 [5] LC_MONETARY=en_US.UTF-8       LC_MESSAGES=en_US.UTF-8      
 [7] LC_PAPER=en_US.UTF-8          LC_NAME=en_US.UTF-8          
 [9] LC_ADDRESS=en_US.UTF-8        LC_TELEPHONE=en_US.UTF-8     
[11] LC_MEASUREMENT=en_US.UTF-8    LC_IDENTIFICATION=en_US.UTF-8

time zone: America/Denver
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ranger_0.15.1       clustifyr_1.12.0    clustifyrdata_1.1.0
 [4] gprofiler2_0.2.2    ggtext_0.1.2        patchwork_1.1.3    
 [7] scales_1.2.1        M3Drop_1.26.0       numDeriv_2016.8-1.1
[10] openxlsx_4.2.5.2    xlsx_0.6.5          MetBrewer_0.2.0    
[13] presto_1.0.0        data.table_1.14.8   Rcpp_1.0.11        
[16] cowplot_1.1.1       knitr_1.44          colorblindr_0.1.0  
[19] colorspace_2.1-0    qs_0.25.5           ggforce_0.4.1      
[22] ggtrace_0.2.0.9000  djvdj_0.1.0         lubridate_1.9.3    
[25] forcats_1.0.0       stringr_1.5.0       dplyr_1.1.3        
[28] purrr_1.0.2         readr_2.1.4         tidyr_1.3.0        
[31] tibble_3.2.1        ggplot2_3.4.4       tidyverse_2.0.0    
[34] here_1.0.1          SeuratObject_4.1.4  Seurat_4.4.0       
[37] biomaRt_2.56.1     

loaded via a namespace (and not attached):
  [1] matrixStats_1.0.0           spatstat.sparse_3.0-2      
  [3] bitops_1.0-7                httr_1.4.7                 
  [5] RColorBrewer_1.1-3          tools_4.3.1                
  [7] sctransform_0.4.0           backports_1.4.1            
  [9] utf8_1.2.3                  R6_2.5.1                   
 [11] lazyeval_0.2.2              uwot_0.1.16                
 [13] mgcv_1.8-42                 withr_2.5.1                
 [15] sp_2.1-0                    prettyunits_1.2.0          
 [17] gridExtra_2.3               progressr_0.14.0           
 [19] cli_3.6.1                   Biobase_2.60.0             
 [21] spatstat.explore_3.2-3      labeling_0.4.3             
 [23] entropy_1.3.1               sass_0.4.7                 
 [25] mvtnorm_1.2-3               spatstat.data_3.0-1        
 [27] ggridges_0.5.4              pbapply_1.7-2              
 [29] QuickJSR_1.0.7              StanHeaders_2.26.28        
 [31] foreign_0.8-84              parallelly_1.36.0          
 [33] bbmle_1.0.25                rstudioapi_0.15.0          
 [35] RSQLite_2.3.1               generics_0.1.3             
 [37] RApiSerialize_0.1.2         gtools_3.9.4               
 [39] ica_1.0-3                   spatstat.random_3.1-6      
 [41] zip_2.3.0                   inline_0.3.19              
 [43] loo_2.6.0                   Matrix_1.6-1.1             
 [45] fansi_1.0.5                 S4Vectors_0.38.2           
 [47] abind_1.4-5                 lifecycle_1.0.3            
 [49] yaml_2.3.7                  SummarizedExperiment_1.30.2
 [51] gplots_3.1.3                BiocFileCache_2.8.0        
 [53] Rtsne_0.16                  grid_4.3.1                 
 [55] blob_1.2.4                  promises_1.2.1             
 [57] crayon_1.5.2                bdsmatrix_1.3-6            
 [59] reldist_1.7-2               miniUI_0.1.1.1             
 [61] densEstBayes_1.0-2.2        lattice_0.21-8             
 [63] xlsxjars_0.6.1              KEGGREST_1.40.1            
 [65] pillar_1.9.0                fgsea_1.26.0               
 [67] GenomicRanges_1.52.1        future.apply_1.11.0        
 [69] codetools_0.2-19            fastmatch_1.1-4            
 [71] leiden_0.4.3                glue_1.6.2                 
 [73] vctrs_0.6.3                 png_0.1-8                  
 [75] gtable_0.3.4                cachem_1.0.8               
 [77] xfun_0.40                   S4Arrays_1.0.6             
 [79] mime_0.12                   survival_3.5-5             
 [81] SingleCellExperiment_1.22.0 rJava_1.0-6                
 [83] statmod_1.5.0               ellipsis_0.3.2             
 [85] fitdistrplus_1.1-11         ROCR_1.0-11                
 [87] nlme_3.1-162                bit64_4.0.5                
 [89] progress_1.2.2              filelock_1.0.2             
 [91] RcppAnnoy_0.0.21            rstan_2.32.3               
 [93] GenomeInfoDb_1.36.4         rprojroot_2.0.3            
 [95] bslib_0.5.1                 irlba_2.3.5.1              
 [97] KernSmooth_2.23-21          rpart_4.1.19               
 [99] BiocGenerics_0.46.0         DBI_1.1.3                  
[101] Hmisc_5.1-1                 nnet_7.3-19                
[103] processx_3.8.2              tidyselect_1.2.0           
[105] bit_4.0.5                   compiler_4.3.1             
[107] curl_5.1.0                  htmlTable_2.4.2            
[109] xml2_1.3.5                  DelayedArray_0.26.7        
[111] plotly_4.10.2               stringfish_0.15.8          
[113] checkmate_2.3.0             caTools_1.18.2             
[115] lmtest_0.9-40               callr_3.7.3                
[117] rappdirs_0.3.3              digest_0.6.33              
[119] goftest_1.2-3               spatstat.utils_3.0-3       
[121] rmarkdown_2.25              XVector_0.40.0             
[123] htmltools_0.5.6.1           pkgconfig_2.0.3            
[125] base64enc_0.1-3             MatrixGenerics_1.12.3      
[127] dbplyr_2.3.4                fastmap_1.1.1              
[129] rlang_1.1.1                 htmlwidgets_1.6.2          
[131] shiny_1.7.5                 farver_2.1.1               
[133] jquerylib_0.1.4             zoo_1.8-12                 
[135] jsonlite_1.8.7              BiocParallel_1.34.2        
[137] RCurl_1.98-1.12             magrittr_2.0.3             
[139] Formula_1.2-5               GenomeInfoDbData_1.2.10    
[141] munsell_0.5.0               reticulate_1.32.0          
[143] stringi_1.7.12              zlibbioc_1.46.0            
[145] MASS_7.3-60                 plyr_1.8.9                 
[147] pkgbuild_1.4.2              parallel_4.3.1             
[149] listenv_0.9.0               ggrepel_0.9.3              
[151] deldir_1.0-9                Biostrings_2.68.1          
[153] splines_4.3.1               gridtext_0.1.5             
[155] tensor_1.5                  hms_1.1.3                  
[157] ps_1.7.5                    igraph_1.5.1               
[159] spatstat.geom_3.2-5         reshape2_1.4.4             
[161] stats4_4.3.1                rstantools_2.3.1.1         
[163] XML_3.99-0.14               evaluate_0.22              
[165] RcppParallel_5.1.7          tzdb_0.4.0                 
[167] tweenr_2.0.2                httpuv_1.6.11              
[169] RANN_2.6.1                  polyclip_1.10-6            
[171] future_1.33.0               scattermore_1.2            
[173] xtable_1.8-4                later_1.3.1                
[175] viridisLite_0.4.2           memoise_2.0.1              
[177] AnnotationDbi_1.62.2        IRanges_2.34.1             
[179] cluster_2.1.4               timechange_0.2.0           
[181] globals_0.16.2